The rapid growth of molecular diagnostics, bioinformatics, and artificial intelligence (AI)/machine learning (ML) has transformed laboratory science, but how far accredited medical laboratory science programs in the United States have adopted their education and training requirements to these advances is still unclear. Using Rogers' Diffusion of Innovation framework, we conducted a nationwide review of 489 program websites and a voluntary Qualtrics survey of 67 program directors. Website data showed that 46.3% of programs offered molecular diagnostics coursework, while bioinformatics (0.8%) and AI (0.2%) content were nearly absent. Survey results supported this pattern. Directors rated sequencing and AI-based tools as increasingly important for workforce readiness. Still, they reported significant barriers to adoption, including limited curriculum time (86.6%), lack of faculty expertise (68.7%), budget constraints (68.7%), and insufficient infrastructure (67.2%). Programs that incorporated molecular diagnostics required significantly more total credits and longer program duration. The findings indicate that molecular content has entered the early majority phase of adoption, while computational technologies remain confined to early innovators. To address these gaps, directors emphasized the need for standardized national curriculum guidelines, expanded faculty training, and stronger institutional support. This study highlights the urgent need for coordinated educational strategies to prepare graduates for the growing molecular and computational demands of the modern clinical laboratory.
Muslu et al. (Wed,) studied this question.